Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes well beyond the annotations by disclosing account/paid-plan requirements, parallel decomposition behavior, return packet fields, explicit gaps[], contradictions[], resolvable citation_uri behavior, semantic excerpting of large records, and 15-90s latency. This is substantial behavioral context that annotations alone do not provide, and there is no contradiction with the readOnly/openWorld/idempotent hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well-structured and front-loaded with auth constraints before moving to core behavior, depth semantics, and output details. A small amount of redundancy exists around pipeworx:// citations, but each section serves a functional purpose for an agent deciding whether and how to invoke the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully explains what the tool returns: a findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], and hop fields. It also covers failure/limitation behavior ('never invented'), timing expectations, and depth-dependent execution, making the tool safely and correctly callable from the description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema covers both parameters, the description enriches them significantly: question is explained as accepting broad/multi-part natural language, and depth is explained behaviorally ('quick=3', standard adds a gap-recovery hop and contradictions[], thorough is paid and chases leads). This goes beyond the schema's enum descriptions and clarifies exactly what each depth value affects.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource ('Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources') and a specific mechanism ('Decomposes your question into focused facets... routes each to the right tool IN PARALLEL'). It explicitly distinguishes itself from open-web search and from ask_pipeworx, saying 'For a single lookup use ask_pipeworx instead,' so an agent can clearly identify what this tool is and is not.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage conditions are explicit: account sign-in is required, unpaid users should 'use ask_pipeworx instead,' and single-lookup questions should use ask_pipeworx. It also gives positive guidance with 'Best for broad/multi-part questions over structured data' and provides concrete examples, plus depth-level selection criteria and expected latency.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.